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Investigating the effective factors in creatinine changes among hemodialysis patients using the linear random effects model
Background and objectives:Out of 10 apparently healthy humans, one was somewhat suffering from one of the types of renal disease. Hemodialysis is known as the most applicable method of taking care of this group of patients. In addition, serum creatinine is an important mark in the performance of kid...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Carol Davila University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5327714/ https://www.ncbi.nlm.nih.gov/pubmed/28255403 |
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author | Shabankhani, B Kazemnezhad, A Zaeri, F |
author_facet | Shabankhani, B Kazemnezhad, A Zaeri, F |
author_sort | Shabankhani, B |
collection | PubMed |
description | Background and objectives:Out of 10 apparently healthy humans, one was somewhat suffering from one of the types of renal disease. Hemodialysis is known as the most applicable method of taking care of this group of patients. In addition, serum creatinine is an important mark in the performance of kidneys. The aim of the present study was to investigate the effective factors in creatinine and its effect on the performance of kidneys. Materials and methods: The present study is a longitudinal experiment in which 500 participants were randomly selected from the hemodialysis patients in Mazandaran Province. Creatinine variable was considered as the longitudinal responding variable, which was measured 3 times per year over a period of 6 years. The random effects model was also considered the most appropriate model for the collected data. Results:The total mean value of creatinine was 1.62 ± 0.49, among men 1.69 ± 0.46 and among women 35.1 ± 0.49. Variables of weight (p<0.001), age of disease diagnosis (p<0.001), time (p<0.001), gender (p<0.005), and cardiovascular diseases were significant and had effects on the trend of creatinine changes among the hemodialysis patients. Creatinine mean value had an increasing trend. Conclusion:Blood creatinine had a significant effect on the performance of kidneys, and the identification of variables that affected the creatinine level was highly helpful in controlling the performance of the kidneys. The results of most studies conducted on hemodialysis patients indicated that by measuring and controlling variables like weight, tobacco consumption, and control of related diseases like blood pressure could predict and control creatinine changes precisely. |
format | Online Article Text |
id | pubmed-5327714 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Carol Davila University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-53277142017-03-02 Investigating the effective factors in creatinine changes among hemodialysis patients using the linear random effects model Shabankhani, B Kazemnezhad, A Zaeri, F J Med Life General Articles Background and objectives:Out of 10 apparently healthy humans, one was somewhat suffering from one of the types of renal disease. Hemodialysis is known as the most applicable method of taking care of this group of patients. In addition, serum creatinine is an important mark in the performance of kidneys. The aim of the present study was to investigate the effective factors in creatinine and its effect on the performance of kidneys. Materials and methods: The present study is a longitudinal experiment in which 500 participants were randomly selected from the hemodialysis patients in Mazandaran Province. Creatinine variable was considered as the longitudinal responding variable, which was measured 3 times per year over a period of 6 years. The random effects model was also considered the most appropriate model for the collected data. Results:The total mean value of creatinine was 1.62 ± 0.49, among men 1.69 ± 0.46 and among women 35.1 ± 0.49. Variables of weight (p<0.001), age of disease diagnosis (p<0.001), time (p<0.001), gender (p<0.005), and cardiovascular diseases were significant and had effects on the trend of creatinine changes among the hemodialysis patients. Creatinine mean value had an increasing trend. Conclusion:Blood creatinine had a significant effect on the performance of kidneys, and the identification of variables that affected the creatinine level was highly helpful in controlling the performance of the kidneys. The results of most studies conducted on hemodialysis patients indicated that by measuring and controlling variables like weight, tobacco consumption, and control of related diseases like blood pressure could predict and control creatinine changes precisely. Carol Davila University Press 2015 /pmc/articles/PMC5327714/ /pubmed/28255403 Text en ©Carol Davila University Press http://creativecommons.org/licenses/by/2.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | General Articles Shabankhani, B Kazemnezhad, A Zaeri, F Investigating the effective factors in creatinine changes among hemodialysis patients using the linear random effects model |
title | Investigating the effective factors in creatinine changes among
hemodialysis patients using the linear random effects model |
title_full | Investigating the effective factors in creatinine changes among
hemodialysis patients using the linear random effects model |
title_fullStr | Investigating the effective factors in creatinine changes among
hemodialysis patients using the linear random effects model |
title_full_unstemmed | Investigating the effective factors in creatinine changes among
hemodialysis patients using the linear random effects model |
title_short | Investigating the effective factors in creatinine changes among
hemodialysis patients using the linear random effects model |
title_sort | investigating the effective factors in creatinine changes among
hemodialysis patients using the linear random effects model |
topic | General Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5327714/ https://www.ncbi.nlm.nih.gov/pubmed/28255403 |
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